Switchable protection and exposure of a sensitive squaraine dye within a redox active rotaxane

In nature, molecular environments in proteins can sterically protect and stabilize reactive species such as organic radicals through non-covalent interactions. Here, we report a near-infrared fluorescent rotaxane in which the stabilization of a chemically labile squaraine fluorophore by the coordination of a tetralactam macrocycle can be controlled chemically and electrochemically. The rotaxane can be switched between two co-conformations in which the wheel either stabilizes or exposes the fluorophore. Coordination by the wheel affects the squaraine’s stability across four redox states and renders the radical anion significantly more stable—by a factor of 6.7—than without protection by a mechanically bonded wheel. Furthermore, the fluorescence properties can be tuned by the redox reactions in a stepwise manner. Mechanically interlocked molecules provide an excellent scaffold to stabilize and selectively expose reactive species in a co-conformational switching process controlled by external stimuli

Designing websites with eXtensible web (xWeb) methodology

Today, eXtensible Markup Language (XML) is fast emerging as the dominant standard for storing, describing, representing and interchanging data among various enterprises systems and databases in the context of complex web enterprises information systems (EIS). Conversely, for web EIS (such as e-commerce and portals) to be successful, it is important to apply a high level, model driven solutions and meta-data vocabularies to design and implementation techniques that are capable of handling heterogonous schemas and documents. For this, we need a methodology that provides a higher level of abstraction of the domain in question with rigorously defined standards that are to be more widely understood by all stakeholders of the system. To-date, UML has proven itself as the language of choice for modeling EIS using OO techniques. With the introduction of XML Schema, which provides rich facilities for constraining and defining enterprise XML content, the combination of UML and XML technologies provide a good platform (and the flexibility) for modeling, designing and representing complex enterprise contents for building successful EIS. In this paper, we show how a layered view model coupled with a proven user interface analysis framework (WUiAM) is utilized in providing architectural construct and abstract website model (called eXtensible Web, xWeb), to model, design and implement simple, user-centred, collaborative websites at varying levels of abstraction. The uniqueness xWeb is that the model data (web user interface definitions, website data descriptions and constraints) and the web content are captured and represented at the conceptual level using views (one model) and can be deployed (multiple platform specific models) using one or more implementation models

Plankton ecology: The past two decades of progress

This is a selected account of recent developments in plankton ecology. The examples have been chosen for their degree of innovation during the past two decades and for their general ecological importance. They range from plankton autecology over interactions between populations to community ecology. The autecology of plankton is represented by the hydromechanics of plankton (the problem of life in a viscous environment) and by the nutritional ecology of phyto- and zooplankton. Population level studies are represented by competition, herbivory (grazing), and zooplankton responses to predation. Community ecology is represented by the debate about bottom- up vs. top-down control of community organization, by the PEG model of seasonal plankton succession, and by the recent discovery of the microbial food web

Climate change effects on phytoplankton depend on cell size and food web structure

We investigated the effects of warming on a natural phytoplankton community from the Baltic Sea, based on six mesocosm experiments conducted 2005–2009. We focused on differences in the dynamics of three phytoplankton size groups which are grazed to a variable extent by different zooplankton groups. While small-sized algae were mostly grazer-controlled, light and nutrient availability largely determined the growth of medium- and large-sized algae. Thus, the latter groups dominated at increased light levels. Warming increased mesozooplankton grazing on medium-sized algae, reducing their biomass. The biomass of small-sized algae was not affected by temperature, probably due to an interplay between indirect effects spreading through the food web. Thus, under the higher temperature and lower light levels anticipated for the next decades in the southern Baltic Sea, a higher share of smaller phytoplankton is expected. We conclude that considering the size structure of the phytoplankton community strongly improves the reliability of projections of climate change effects

Mechanistic origins of variability in phytoplankton dynamics. Part II: analysis of mesocosm blooms under climate change scenarios

Driving factors of phytoplankton spring blooms have been discussed since long, but rarely analyzed quantitatively. Here, we use a mechanistic size-based ecosystem model to reconstruct observations made during the Kiel mesocosm experiments (2005–2006). The model accurately hindcasts highly variable bloom developments including community shifts in cell size. Under low light, phytoplankton dynamics was mostly controlled by selective mesozooplankton grazing. Selective grazing also explains initial dominance of large diatoms under high light conditions. All blooms were mainly terminated by aggregation and sedimentation. Allometries in nutrient uptake capabilities led to a delayed, post-bloom dominance of small species. In general, biomass and trait dynamics revealed many mutual dependencies, while growth factors decoupled from the respective selective forces. A size shift induced by one factor often changed the growth dependency on other factors. Within climate change scenarios, these indirect effects produced large sensitivities of ecosystem fluxes to the size distribution of winter phytoplankton. These sensitivities exceeded those found for changes in vertical mixing, whereas temperature changes only had minimal impacts

Long-term cyclic persistence in an experimental predator–prey system

Predator–prey cycles rank among the most fundamental concepts in ecology, are predicted by the simplest ecological models and enable, theoretically, the indefinite persistence of predator and prey1,2,3,4. However, it remains an open question for how long cyclic dynamics can be self-sustained in real communities. Field observations have been restricted to a few cycle periods5,6,7,8 and experimental studies indicate that oscillations may be short-lived without external stabilizing factors9,10,11,12,13,14,15,16,17,18,19. Here we performed microcosm experiments with a planktonic predator–prey system and repeatedly observed oscillatory time series of unprecedented length that persisted for up to around 50 cycles or approximately 300 predator generations. The dominant type of dynamics was characterized by regular, coherent oscillations with a nearly constant predator–prey phase difference. Despite constant experimental conditions, we also observed shorter episodes of irregular, non-coherent oscillations without any significant phase relationship. However, the predator–prey system showed a strong tendency to return to the dominant dynamical regime with a defined phase relationship. A mathematical model suggests that stochasticity is probably responsible for the reversible shift from coherent to non-coherent oscillations, a notion that was supported by experiments with external forcing by pulsed nutrient supply. Our findings empirically demonstrate the potential for infinite persistence of predator and prey populations in a cyclic dynamic regime that shows resilience in the presence of stochastic events

Dome patterns in pelagic size spectra reveal strong trophic cascades

In ecological communities, especially the pelagic zones of aquatic ecosystems, certain bodysize ranges are often over-represented compared to others. Community size spectra, the distributions of community biomass over the logarithmic body-mass axis, tend to exhibit regularly spaced local maxima, called "domes", separated by steep troughs. Contrasting established theory, we explain these dome patterns as manifestations of top-down trophic cascades along aquatic food chains. Compiling high quality size-spectrum data and comparing these with a size-spectrum model introduced in this study, we test this theory and develop a detailed picture of the mechanisms by which bottom-up and top-down effects interact to generate dome patterns. Results imply that strong top-down trophic cascades are common in freshwater communities, much more than hitherto demonstrated, and may arise in nutrient rich marine systems as well. Transferring insights from the general theory of nonlinear pattern formation to domes patterns, we provide new interpretations of past lake-manipulation experiments

The intrinsic predictability of ecological time series and its potential to guide forecasting

Successfully predicting the future states of systems that are complex, stochastic and potentially chaotic is a major challenge. Model forecasting error (FE) is the usual measure of success; however model predictions provide no insights into the potential for improvement. In short, the realized predictability of a specific model is uninformative about whether the system is inherently predictable or whether the chosen model is a poor match for the system and our observations thereof. Ideally, model proficiency would be judged with respect to the systems’ intrinsic predictability – the highest achievable predictability given the degree to which system dynamics are the result of deterministic v. stochastic processes. Intrinsic predictability may be quantified with permutation entropy (PE), a model‐free, information‐theoretic measure of the complexity of a time series. By means of simulations we show that a correlation exists between estimated PE and FE and show how stochasticity, process error, and chaotic dynamics affect the relationship. This relationship is verified for a dataset of 461 empirical ecological time series. We show how deviations from the expected PE‐FE relationship are related to covariates of data quality and the nonlinearity of ecological dynamics. These results demonstrate a theoretically‐grounded basis for a model‐free evaluation of a system's intrinsic predictability. Identifying the gap between the intrinsic and realized predictability of time series will enable researchers to understand whether forecasting proficiency is limited by the quality and quantity of their data or the ability of the chosen forecasting model to explain the data. Intrinsic predictability also provides a model‐free baseline of forecasting proficiency against which modeling efforts can be evaluated

Sheldon Spectrum and the Plankton Paradox: Two Sides of the Same Coin : A trait-based plankton size-spectrum model

The Sheldon spectrum describes a remarkable regularity in aquatic ecosystems: the biomass density as a function of logarithmic body mass is approximately constant over many orders of magnitude. While size-spectrum models have explained this phenomenon for assemblages of multicellular organisms, this paper introduces a species-resolved size-spectrum model to explain the phenomenon in unicellular plankton. A Sheldon spectrum spanning the cell-size range of unicellular plankton necessarily consists of a large number of coexisting species covering a wide range of characteristic sizes. The coexistence of many phytoplankton species feeding on a small number of resources is known as the Paradox of the Plankton. Our model resolves the paradox by showing that coexistence is facilitated by the allometric scaling of four physiological rates. Two of the allometries have empirical support, the remaining two emerge from predator-prey interactions exactly when the abundances follow a Sheldon spectrum. Our plankton model is a scale-invariant trait-based size-spectrum model: it describes the abundance of phyto- and zooplankton cells as a function of both size and species trait (the maximal size before cell division). It incorporates growth due to resource consumption and predation on smaller cells, death due to predation, and a flexible cell division process. We give analytic solutions at steady state for both the within-species size distributions and the relative abundances across species